Service repositories, such as the Enterprise Service Workplace (ESW), provide access to large numbers of documents (i.e., Enterprise Services) to business users and program development users. However, because some users might not be familiar with a particular domain and its terminology, entering appropriate search terms to quickly retrieve relevant documents can be a challenging task. In an attempt to address this problem, repositories often provide search opportunities intended to assist users in finding their desired documents. Within this context, users express their search criteria in natural language (i.e., ordinary language that is non-specific to a particular domain) using a small set of discriminating keywords. As a part of an ontology-based keyword search, the keywords are then expanded with additional semantic relationships and compared against annotations associated with the Enterprise Services. Although ontology-based keyword searches can generate several results, they typically lack accuracy and precision and/or do not capture the true meaning of a user's query. Retrieving appropriate search results can be further complicated by the fact that natural language can be unclear (e.g., due to the inclusion of homonyms, synonyms, etc.) and requires disambiguation to correctly determine related concepts.